@article{RN494,
   author = {Yang, C. and Williams, R. D. and Swerdel, J. N. and Almeida, J. R. and Brouwer, E. S. and Burn, E. and Carmona, L. and Chatzidionysiou, K. and Duarte-Salles, T. and Fakhouri, W. and Hottgenroth, A. and Jani, M. and Kolde, R. and Kors, J. A. and Kullamaa, L. and Lane, J. and Marinier, K. and Michel, A. and Stewart, H. M. and Prats-Uribe, A. and Reisberg, S. and Sena, A. G. and Torre, C. O. and Verhamme, K. and Vizcaya, D. and Weaver, J. and Ryan, P. and Prieto-Alhambra, D. and Rijnbeek, P. R.},
   title = {Development and external validation of prediction models for adverse health outcomes in rheumatoid arthritis: A multinational real-world cohort analysis},
   journal = {Semin Arthritis Rheum},
   volume = {56},
   pages = {152050},
   note = {1532-866x Yang, Cynthia Williams, Ross D Swerdel, Joel N Almeida, João Rafael Brouwer, Emily S Burn, Edward Carmona, Loreto Chatzidionysiou, Katerina Duarte-Salles, Talita Fakhouri, Walid Hottgenroth, Antje Jani, Meghna Kolde, Raivo Kors, Jan A Kullamaa, Lembe Lane, Jennifer Marinier, Karine Michel, Alexander Stewart, Henry Morgan Prats-Uribe, Albert Reisberg, Sulev Sena, Anthony G Torre, Carmen O Verhamme, Katia Vizcaya, David Weaver, James Ryan, Patrick Prieto-Alhambra, Daniel Rijnbeek, Peter R 21605/VAC_/Versus Arthritis/United Kingdom DH_/Department of Health/United Kingdom Journal Article Research Support, Non-U.S. Gov't United States 2022/06/22 Semin Arthritis Rheum. 2022 Oct;56:152050. doi: 10.1016/j.semarthrit.2022.152050. Epub 2022 Jun 15.},
   abstract = {BACKGROUND: Identification of rheumatoid arthritis (RA) patients at high risk of adverse health outcomes remains a major challenge. We aimed to develop and validate prediction models for a variety of adverse health outcomes in RA patients initiating first-line methotrexate (MTX) monotherapy. METHODS: Data from 15 claims and electronic health record databases across 9 countries were used. Models were developed and internally validated on Optum® De-identified Clinformatics® Data Mart Database using L1-regularized logistic regression to estimate the risk of adverse health outcomes within 3 months (leukopenia, pancytopenia, infection), 2 years (myocardial infarction (MI) and stroke), and 5 years (cancers [colorectal, breast, uterine] after treatment initiation. Candidate predictors included demographic variables and past medical history. Models were externally validated on all other databases. Performance was assessed using the area under the receiver operator characteristic curve (AUC) and calibration plots. FINDINGS: Models were developed and internally validated on 21,547 RA patients and externally validated on 131,928 RA patients. Models for serious infection (AUC: internal 0.74, external ranging from 0.62 to 0.83), MI (AUC: internal 0.76, external ranging from 0.56 to 0.82), and stroke (AUC: internal 0.77, external ranging from 0.63 to 0.95), showed good discrimination and adequate calibration. Models for the other outcomes showed modest internal discrimination (AUC < 0.65) and were not externally validated. INTERPRETATION: We developed and validated prediction models for a variety of adverse health outcomes in RA patients initiating first-line MTX monotherapy. Final models for serious infection, MI, and stroke demonstrated good performance across multiple databases and can be studied for clinical use. FUNDING: This activity under the European Health Data & Evidence Network (EHDEN) has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806968. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA.},
   keywords = {*Antirheumatic Agents/therapeutic use
*Arthritis, Rheumatoid/drug therapy
Cohort Studies
Humans
Methotrexate/therapeutic use
Outcome Assessment, Health Care
*Stroke/etiology
Cardiovascular diseases
Infections
Methotrexate
Prediction models
Rheumatoid arthritis ,
ISSN = 0049-0172 ,
DOI = 10.1016/j.semarthrit.2022.152050},
   year = {2022},
   type = {Journal Article}
}

{"_id":"WaCq3uf5eZ24ywEyT","bibbaseid":"yang-williams-swerdel-almeida-brouwer-burn-carmona-chatzidionysiou-etal-developmentandexternalvalidationofpredictionmodelsforadversehealthoutcomesinrheumatoidarthritisamultinationalrealworldcohortanalysis-2022","author_short":["Yang, C.","Williams, R. D.","Swerdel, J. N.","Almeida, J. R.","Brouwer, E. S.","Burn, E.","Carmona, L.","Chatzidionysiou, K.","Duarte-Salles, T.","Fakhouri, W.","Hottgenroth, A.","Jani, M.","Kolde, R.","Kors, J. A.","Kullamaa, L.","Lane, J.","Marinier, K.","Michel, A.","Stewart, H. M.","Prats-Uribe, A.","Reisberg, S.","Sena, A. G.","Torre, C. O.","Verhamme, K.","Vizcaya, D.","Weaver, J.","Ryan, P.","Prieto-Alhambra, D.","Rijnbeek, P. R."],"bibdata":{"bibtype":"article","type":"Journal Article","author":[{"propositions":[],"lastnames":["Yang"],"firstnames":["C."],"suffixes":[]},{"propositions":[],"lastnames":["Williams"],"firstnames":["R.","D."],"suffixes":[]},{"propositions":[],"lastnames":["Swerdel"],"firstnames":["J.","N."],"suffixes":[]},{"propositions":[],"lastnames":["Almeida"],"firstnames":["J.","R."],"suffixes":[]},{"propositions":[],"lastnames":["Brouwer"],"firstnames":["E.","S."],"suffixes":[]},{"propositions":[],"lastnames":["Burn"],"firstnames":["E."],"suffixes":[]},{"propositions":[],"lastnames":["Carmona"],"firstnames":["L."],"suffixes":[]},{"propositions":[],"lastnames":["Chatzidionysiou"],"firstnames":["K."],"suffixes":[]},{"propositions":[],"lastnames":["Duarte-Salles"],"firstnames":["T."],"suffixes":[]},{"propositions":[],"lastnames":["Fakhouri"],"firstnames":["W."],"suffixes":[]},{"propositions":[],"lastnames":["Hottgenroth"],"firstnames":["A."],"suffixes":[]},{"propositions":[],"lastnames":["Jani"],"firstnames":["M."],"suffixes":[]},{"propositions":[],"lastnames":["Kolde"],"firstnames":["R."],"suffixes":[]},{"propositions":[],"lastnames":["Kors"],"firstnames":["J.","A."],"suffixes":[]},{"propositions":[],"lastnames":["Kullamaa"],"firstnames":["L."],"suffixes":[]},{"propositions":[],"lastnames":["Lane"],"firstnames":["J."],"suffixes":[]},{"propositions":[],"lastnames":["Marinier"],"firstnames":["K."],"suffixes":[]},{"propositions":[],"lastnames":["Michel"],"firstnames":["A."],"suffixes":[]},{"propositions":[],"lastnames":["Stewart"],"firstnames":["H.","M."],"suffixes":[]},{"propositions":[],"lastnames":["Prats-Uribe"],"firstnames":["A."],"suffixes":[]},{"propositions":[],"lastnames":["Reisberg"],"firstnames":["S."],"suffixes":[]},{"propositions":[],"lastnames":["Sena"],"firstnames":["A.","G."],"suffixes":[]},{"propositions":[],"lastnames":["Torre"],"firstnames":["C.","O."],"suffixes":[]},{"propositions":[],"lastnames":["Verhamme"],"firstnames":["K."],"suffixes":[]},{"propositions":[],"lastnames":["Vizcaya"],"firstnames":["D."],"suffixes":[]},{"propositions":[],"lastnames":["Weaver"],"firstnames":["J."],"suffixes":[]},{"propositions":[],"lastnames":["Ryan"],"firstnames":["P."],"suffixes":[]},{"propositions":[],"lastnames":["Prieto-Alhambra"],"firstnames":["D."],"suffixes":[]},{"propositions":[],"lastnames":["Rijnbeek"],"firstnames":["P.","R."],"suffixes":[]}],"title":"Development and external validation of prediction models for adverse health outcomes in rheumatoid arthritis: A multinational real-world cohort analysis","journal":"Semin Arthritis Rheum","volume":"56","pages":"152050","note":"1532-866x Yang, Cynthia Williams, Ross D Swerdel, Joel N Almeida, João Rafael Brouwer, Emily S Burn, Edward Carmona, Loreto Chatzidionysiou, Katerina Duarte-Salles, Talita Fakhouri, Walid Hottgenroth, Antje Jani, Meghna Kolde, Raivo Kors, Jan A Kullamaa, Lembe Lane, Jennifer Marinier, Karine Michel, Alexander Stewart, Henry Morgan Prats-Uribe, Albert Reisberg, Sulev Sena, Anthony G Torre, Carmen O Verhamme, Katia Vizcaya, David Weaver, James Ryan, Patrick Prieto-Alhambra, Daniel Rijnbeek, Peter R 21605/VAC_/Versus Arthritis/United Kingdom DH_/Department of Health/United Kingdom Journal Article Research Support, Non-U.S. Gov't United States 2022/06/22 Semin Arthritis Rheum. 2022 Oct;56:152050. doi: 10.1016/j.semarthrit.2022.152050. Epub 2022 Jun 15.","abstract":"BACKGROUND: Identification of rheumatoid arthritis (RA) patients at high risk of adverse health outcomes remains a major challenge. We aimed to develop and validate prediction models for a variety of adverse health outcomes in RA patients initiating first-line methotrexate (MTX) monotherapy. METHODS: Data from 15 claims and electronic health record databases across 9 countries were used. Models were developed and internally validated on Optum® De-identified Clinformatics® Data Mart Database using L1-regularized logistic regression to estimate the risk of adverse health outcomes within 3 months (leukopenia, pancytopenia, infection), 2 years (myocardial infarction (MI) and stroke), and 5 years (cancers [colorectal, breast, uterine] after treatment initiation. Candidate predictors included demographic variables and past medical history. Models were externally validated on all other databases. Performance was assessed using the area under the receiver operator characteristic curve (AUC) and calibration plots. FINDINGS: Models were developed and internally validated on 21,547 RA patients and externally validated on 131,928 RA patients. Models for serious infection (AUC: internal 0.74, external ranging from 0.62 to 0.83), MI (AUC: internal 0.76, external ranging from 0.56 to 0.82), and stroke (AUC: internal 0.77, external ranging from 0.63 to 0.95), showed good discrimination and adequate calibration. Models for the other outcomes showed modest internal discrimination (AUC < 0.65) and were not externally validated. INTERPRETATION: We developed and validated prediction models for a variety of adverse health outcomes in RA patients initiating first-line MTX monotherapy. Final models for serious infection, MI, and stroke demonstrated good performance across multiple databases and can be studied for clinical use. FUNDING: This activity under the European Health Data & Evidence Network (EHDEN) has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806968. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA.","keywords":"*Antirheumatic Agents/therapeutic use *Arthritis, Rheumatoid/drug therapy Cohort Studies Humans Methotrexate/therapeutic use Outcome Assessment, Health Care *Stroke/etiology Cardiovascular diseases Infections Methotrexate Prediction models Rheumatoid arthritis , ISSN = 0049-0172 , DOI = 10.1016/j.semarthrit.2022.152050","year":"2022","bibtex":"@article{RN494,\r\n author = {Yang, C. and Williams, R. D. and Swerdel, J. N. and Almeida, J. R. and Brouwer, E. S. and Burn, E. and Carmona, L. and Chatzidionysiou, K. and Duarte-Salles, T. and Fakhouri, W. and Hottgenroth, A. and Jani, M. and Kolde, R. and Kors, J. A. and Kullamaa, L. and Lane, J. and Marinier, K. and Michel, A. and Stewart, H. M. and Prats-Uribe, A. and Reisberg, S. and Sena, A. G. and Torre, C. O. and Verhamme, K. and Vizcaya, D. and Weaver, J. and Ryan, P. and Prieto-Alhambra, D. and Rijnbeek, P. R.},\r\n title = {Development and external validation of prediction models for adverse health outcomes in rheumatoid arthritis: A multinational real-world cohort analysis},\r\n journal = {Semin Arthritis Rheum},\r\n volume = {56},\r\n pages = {152050},\r\n note = {1532-866x Yang, Cynthia Williams, Ross D Swerdel, Joel N Almeida, João Rafael Brouwer, Emily S Burn, Edward Carmona, Loreto Chatzidionysiou, Katerina Duarte-Salles, Talita Fakhouri, Walid Hottgenroth, Antje Jani, Meghna Kolde, Raivo Kors, Jan A Kullamaa, Lembe Lane, Jennifer Marinier, Karine Michel, Alexander Stewart, Henry Morgan Prats-Uribe, Albert Reisberg, Sulev Sena, Anthony G Torre, Carmen O Verhamme, Katia Vizcaya, David Weaver, James Ryan, Patrick Prieto-Alhambra, Daniel Rijnbeek, Peter R 21605/VAC_/Versus Arthritis/United Kingdom DH_/Department of Health/United Kingdom Journal Article Research Support, Non-U.S. Gov't United States 2022/06/22 Semin Arthritis Rheum. 2022 Oct;56:152050. doi: 10.1016/j.semarthrit.2022.152050. Epub 2022 Jun 15.},\r\n abstract = {BACKGROUND: Identification of rheumatoid arthritis (RA) patients at high risk of adverse health outcomes remains a major challenge. We aimed to develop and validate prediction models for a variety of adverse health outcomes in RA patients initiating first-line methotrexate (MTX) monotherapy. METHODS: Data from 15 claims and electronic health record databases across 9 countries were used. Models were developed and internally validated on Optum® De-identified Clinformatics® Data Mart Database using L1-regularized logistic regression to estimate the risk of adverse health outcomes within 3 months (leukopenia, pancytopenia, infection), 2 years (myocardial infarction (MI) and stroke), and 5 years (cancers [colorectal, breast, uterine] after treatment initiation. Candidate predictors included demographic variables and past medical history. Models were externally validated on all other databases. Performance was assessed using the area under the receiver operator characteristic curve (AUC) and calibration plots. FINDINGS: Models were developed and internally validated on 21,547 RA patients and externally validated on 131,928 RA patients. Models for serious infection (AUC: internal 0.74, external ranging from 0.62 to 0.83), MI (AUC: internal 0.76, external ranging from 0.56 to 0.82), and stroke (AUC: internal 0.77, external ranging from 0.63 to 0.95), showed good discrimination and adequate calibration. Models for the other outcomes showed modest internal discrimination (AUC < 0.65) and were not externally validated. INTERPRETATION: We developed and validated prediction models for a variety of adverse health outcomes in RA patients initiating first-line MTX monotherapy. Final models for serious infection, MI, and stroke demonstrated good performance across multiple databases and can be studied for clinical use. FUNDING: This activity under the European Health Data & Evidence Network (EHDEN) has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806968. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA.},\r\n keywords = {*Antirheumatic Agents/therapeutic use\r\n*Arthritis, Rheumatoid/drug therapy\r\nCohort Studies\r\nHumans\r\nMethotrexate/therapeutic use\r\nOutcome Assessment, Health Care\r\n*Stroke/etiology\r\nCardiovascular diseases\r\nInfections\r\nMethotrexate\r\nPrediction models\r\nRheumatoid arthritis ,\r\nISSN = 0049-0172 ,\r\nDOI = 10.1016/j.semarthrit.2022.152050},\r\n year = {2022},\r\n type = {Journal Article}\r\n}\r\n\r\n","author_short":["Yang, C.","Williams, R. D.","Swerdel, J. N.","Almeida, J. R.","Brouwer, E. S.","Burn, E.","Carmona, L.","Chatzidionysiou, K.","Duarte-Salles, T.","Fakhouri, W.","Hottgenroth, A.","Jani, M.","Kolde, R.","Kors, J. 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